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Information Systems and Artificial Intelligence

Information Systems and Artificial Intelligence


Information Systems and Artificial Intelligence: Explore the relationship between information systems and artificial intelligence (AI). You could discuss how AI is being used to develop new information systems and how information systems are being used to support the development of AI.


  1. Introduction

During the last three decades, a good deal of confusion has surrounded the term ‘Information Systems’. This term has been used broadly to cover the utilization of Information Technology (IT) by business users of all sorts. Frequently it has been used for the more narrow description of computer-based information systems (CBIS) which will be dealt with in section 1.1. Even in CBIS, the terminological difficulties do not cease. Many technical and complex terms have been employed to describe systems and there is frequently little agreement as to the meaning of these. In the context of Artificial Intelligence, the word ‘information systems’ has been used to describe systems which are in essence AI systems. These systems attempt to use a computer to manipulate knowledge and data that a human would use in some intelligent way, for example to produce a diagnosis or to solve a complex problem. Whatever the system called, the new wave of AI systems which are information systems suggest that we should re-examine the ways in which we develop systems and the theoretical frameworks that underpin this development. This is bound to have a beneficial effect on conventional information systems and it may well make it easier to understand what has been done in the past and what will be done in the future.

1.1. Definition of Information Systems

Information systems are an integrated set of components for collecting, storing, and processing data and for delivering information, knowledge, and digital products. Businesses, other organizations, and individuals in contemporary society typically rely on information systems to manage their operations, compete in the marketplace, provide services, and augment personal lives. Built on a solid infrastructure of computer hardware, software, data, and networks, information systems play a critical role in the competitive and the general well-being of an organization or society. Information systems are frequently considered only in the context of organizational operations or in the context of data storage and retrieval systems. This can be misleading. We will consider information systems in a broader sense than simply record keeping or data processing. In this view, an information system collects, processes, stores, analyzes, and disseminates information for a specific purpose.

1.2. Definition of Artificial Intelligence

“AI can be defined as ‘narrow’ if it is performing a specific intelligent task using methods that are applicable only to that task and are not intended to simulate human cognition. AI is ‘general’ if it simulates human cognition in thought and action” (Luger and Stubblefield, 2004). This represents a dichotomy in the field of AI. AI systems that are not simulating human cognition are already prevalent and hugely successful. Techniques in these systems have taught us much about problem-solving and have led to the development of tools that are extremely useful. An example would be the ‘simplex’ algorithm for linear programming. This is an advanced method for finding the best solution from all possible solutions to maximize or minimize a linear objective function. It has exact methods and achieves an exact result. Unfortunately, methods in AI continue to be overshadowed and compared to human intelligence techniques. This has led to the stigma in computing circles that AI serves no other purpose than to simulate human cognition. The ultimate evidence of this would be success in writing a program that emulates all human intelligence behavior. Failure to achieve this would leave many to believe that the methods in human cognition were not understood well enough in the first place.

The definition of artificial intelligence (AI) is itself a complex issue. We have, however, at least one iteration of a general definition that will be used as a point of reference. According to Winston (1992), AI is “the study of the computations that make it possible to perceive, reason, and act.” The purpose of AI has been the long-running dream of computer scientists who have developed computer-based systems to solve problems that normally require human intelligence. They have been attempting to replicate reasoning, knowledge, planning, learning, communication, perception, and the ability to move and manipulate objects. In many cases, these systems have vastly outperformed humans in their specific tasks. This has led to a large proportion of AI research being focused on areas that will enable the development of non-intelligent systems to act more intelligently. If we label the overall effort to create computer systems that can execute intelligent tasks, this would cover almost all of AI. This would indicate that a system is intelligent if it can act and prevail in the task it was designed for.

  1. Relationship between Information Systems and Artificial Intelligence

2.1. Overview of the Relationship

2.2. How AI is Used to Develop Information Systems

2.3. How Information Systems Support the Development of AI

  1. Applications of Artificial Intelligence in Information Systems

3.1. AI in Data Analysis and Decision Making

3.2. AI in Natural Language Processing

3.3. AI in Machine Learning

  1. Benefits of Integrating AI into Information Systems

4.1. Improved Efficiency and Accuracy

4.2. Enhanced Decision Making

4.3. Automation of Repetitive Tasks

4.4. Personalized User Experiences

  1. Challenges and Limitations of AI in Information Systems

5.1. Ethical Considerations

5.2. Data Privacy and Security

5.3. Lack of Human Judgment and Intuition

  1. Future Trends and Developments in AI and Information Systems

6.1. Advancements in Machine Learning Algorithms

6.2. Integration of AI with Internet of Things (IoT)

6.3. AI-Powered Chatbots and Virtual Assistants

  1. Case Studies

7.1. AI-Driven Customer Relationship Management (CRM) Systems

7.2. AI-Powered Recommendation Systems

7.3. AI in Healthcare Information Systems

  1. Conclusion


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